Cardiac Magnetic Resonance to Predict Cardiac Mass Malignancy: The CMR Mass Score

BACKGROUND: Multimodality imaging is currently suggested for the noninvasive diagnosis of cardiac masses. The identification of cardiac masses’ malignant nature is essential to guide proper treatment. We aimed to develop a cardiac magnetic resonance (CMR)-derived model including mass localization, morphology, and tissue characterization to predict malignancy (with histology as gold standard), to compare its accuracy versus the diagnostic echocardiographic mass score, and to evaluate its prognostic ability. METHODS: Observational cohort study of 167 consecutive patients undergoing comprehensive echocardiogram and CMR within 1-month time interval for suspected cardiac mass. A definitive diagnosis was achieved by histological examination or, in the case of cardiac thrombi, by histology or radiological resolution after adequate anticoagulation treatment. Logistic regression was performed to assess CMR-derived independent predictors of malignancy, which were included in a predictive model to derive the CMR mass score. Kaplan-Meier curves and Cox regression were used to investigate the prognostic ability of predictors. RESULTS: In CMR, mass morphological features (non-left localization, sessile, polylobate, inhomogeneity, infiltration, and pericardial effusion) and mass tissue characterization features (first-pass perfusion and heterogeneity enhancement) were independent predictors of malignancy. The CMR mass score (range, 0–8 and cutoff, ≥5), including sessile appearance, polylobate shape, infiltration, pericardial effusion, first-pass contrast perfusion, and heterogeneity enhancement, showed excellent accuracy in predicting malignancy (areas under the curve, 0.976 [95% CI, 0.96–0.99]), significantly higher than diagnostic echocardiographic mass score (areas under the curve, 0.932; P=0.040). The agreement between the diagnostic echocardiographic mass and CMR mass scores was good (κ=0.66). A CMR mass score of ≥5 predicted a higher risk of all-cause death (P<0.001; hazard ratio, 5.70) at follow-up. CONCLUSIONS: A CMR-derived model, including mass morphology and tissue characterization, showed excellent accuracy, superior to echocardiography, in predicting cardiac masses malignancy, with prognostic implications.


Definition and classifications of Cardiac Masses
All cases were classified according to the World Health Organization 2015 Classification of Tumors of the Heart and Pericardium (16); sarcomas were graded according to the Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC) system (26,27).Pseudotumors, which represent an extremely heterogeneous group, were defined as lesions not originating from a neoplastic transformation of a specific cell type (28).Normal anatomical variants were excluded due to the inability to obtain a histological examination.Patients with suspected endocarditis underwent laboratory and imaging investigations according to guidelines (29).Only patients with CMs that did not meet the diagnostic criteria for infective endocarditis were included in our Registry.

Pathology
Surgical specimens.Gross evaluation and sampling of surgical specimens were performed following the standard indications for soft tissue tumors: masses up to 5 cm were entirely included; in those over 5 cm, one section per cm was sampled.From a paraffin-embedded block, 2-μm-thick sections were cut and routinely stained with Haematoxylin-Eosin.Biopsy samples.Endomyocardial biopsies (EMB) and small surgical biopsies were rapidly fixed and processed by microwave.Following indications for transplant biopsy monitoring and the 2011 AECVP/SCVP Consensus Statement on EMB, serial sections were obtained, a part of which were stained using Haematoxylin-Eosin and the remainder left unstained for immunohistochemistry and special stainings (30).
Special stains included Alcian blue, Periodic acid-Schiff, Toluidine bleu, Von Kossa for calcium deposits, Mallory Trichrome for collagen, and Weigert-Van Gieson for elastic fibres, where appropriate.
According to tumor type appropriate immunohistochemistry panels were sequentially applied as described in the review by Wei et al (31,32).

Data collection and outcomes
For each patient, demographic and clinical data were collected.All patients underwent a complete diagnostic work-up, including clinical evaluation and laboratory testing (with specific examinations according to the clinical scenario).All patients were followed-up after the index presentation, and clinical data were obtained from outpatient visits or telephone interviews.

Echocardiography
All patients were evaluated by echocardiogram using a high-quality ultrasound machine (iE33, Affinity or Epiq 7C, Philips Healthcare, Eindhoven, The Netherlands).Echocardiographic examination was performed following the recommendations of the American Society of Echocardiography and the European Association of Cardiovascular Imaging with the patients in the left lateral recumbent position with the use of standard views (17-20).At least three consecutive beats were recorded for each view, and all images were stored for offline analysis (Intellispace, Philips Healthcare, Eindhoven, The Netherlands).The recorded images were analyzed offline by expert cardiologists with experience in cardiac imaging, blinded to clinical information and CMs histology.The cardiac imager analyzed all echoes using a pre-specified worksheet to mark the presence or absence of the following parameters: location (left/right, atrium/ventricle, pericardium, great vessels), site of attachment (interatrial/interventricular septum or roof/side wall of the atrium, ventricular free wall), dimension, shape (regular/irregular), margins (well defined/irregular -if more than 50% of the border was clearly demarcated), mass characteristics (sessile -attached directly by the base and not raised upon a stalk, pedunculated -raised upon a stalk -or polylobate -having two or more lobes), mobility, infiltration [defined as disruption of neighboring tissue and extension of the mass across the pericardium into myocardium, with interruption of epicardial and endocardial contours or, alternatively, by the presence of at least one of the following echocardiographic features i) evidence of a different reflectivity compared to the normal myocardium as infiltrating masses usually have a peculiar, granular echocardiographic texture; ii) increased thickness in comparison with the adjacent myocardial segments; iii) hypo/akinesia of a focal myocardial area compared to closest cardiac segments in absence of coronary distribution that could lead to the suspicion of ischemic etiology] (33), pericardial effusion (defined as a fluid accumulation between the two pericardial layers) and echogenicity pattern (hypo-, iso-or hyperechogenic as compared with normal myocardium).Left ventricle end-diastolic diameter (LVEDD) and volume (LVEDV) were calculated according to the ASE and EACVI recommendations (19,20).LVEF was calculated using Simpson's biplane method.LV diastolic function was assessed as recommended by the ASE/EACVI Guidelines, including E wave, e' velocities, E/e', left atrial volume index (LAVi), and tricuspid regurgitation velocity (34).

Cardiac Magnetic Resonance
The ECG-gated balanced steady-state free precession (SSFP) pulse sequence for cine images were acquired in the four-chambers, two-chambers and three-chambers long-axis (LA); in addition, a full stack of short-axis (SA) views was acquired from base to the apex to provide full coverage of the left and right ventricles.The T1-weighted and the T2-weighted inversion recovery fast-spin echo (IR FSE) sequences, images were acquired in identical long-and short-axis views than the cine images.The T1-weighted were repeated with fat saturation pre-pulse, if needed.Following this, an intravenous bolus dose of 0.1 mmol/kg Gd-DTPA (Dimeglumine gadopentetate) was administered at a rate of 5 ml/s by an MRIcompatible power injector, followed by 30ml saline flush (5ml/s).The first-pass perfusion imaging was performed simultaneously with the injection of gadolinium.Immediately after first-pass perfusion imaging, a second bolus dose of 0.1 mmol/kg Gd-DTPA was administered.EGE images were acquired 1-4 minutes after gadolinium injection with a fixed inversion time (TI) of 440 ms (inversion recoveryprepared T1-weighted gradient echo).10 minutes after gadolinium injection, a 'Look Locker' sequence was performed to obtain the most appropriate TI to null the signal intensity of normal myocardium.LGE images were then acquired 10-15 minutes after gadolinium injection with identical pulse sequence parameters as for EGE apart from the specifically determined TI.

Benign vs malignant masses: clinical presentation
Baseline characteristics, cardiovascular risk factors, comorbidities, and clinical presentation are reported in Supplemental Table S1.Age at presentation, body mass index, cardiovascular risk factors, and comorbidities were similar in the two groups.Patients with malignant masses present more frequently with dyspnea -mostly in NYHA Class III/IV -and with a lower rate of incidental diagnosis than benign ones (p<0.001).Moreover, patients with malignant masses exhibited a higher rate of pulmonary embolism (p=0.008).The echocardiographic characteristics of both groups are shown in Supplementary Table S2.

Sensitivity analysis
We tested the predictive accuracy of the CMR Mass Score in our study population, excluding patients with left ventricular thrombus.Among the 24 thrombi included, 8 were in the left ventricle (with the remaining ones being in the right ventricle or in the atrial chambers).Thus, the subset population without LV thrombus included 159 patients.In this subset population, the CMR Mass score was confirmed to have an excellent diagnostic performance in discriminating malignancy of cardiac masses (AUC 0.974, 95% CI 0.95-0.99,p<0.001), which was significantly higher compared to the CMR-derived DEM score (AUC 0.948, 95% CI 0.91-0.98,p<0.001; p-value for comparison 0.03 at DeLong test) (Supplementary Figure S3).

Inter-observer variability
All the 167 CMRs recorded were randomly selected and re-analyzed by a cardiologist in training (a young cardiologist who just completed a 1-year fellowship in cardiac imaging and was at the beginning of his/her career), after an appropriate training session, blinded to patient clinical data.Inter-observer variability of the variables selected for the score (defined as proposed in the Methods Section and expressed as dichotomized data according to the presence or absence in each CMR) was estimated by Cohen's coefficient.Adequate agreement was defined as κ ≥ 0.70.Inter-observer agreement expressed as Cohen's κ was adequate (κ ≥ 0.70) with a percentage of agreement > 85% for all the parameters selected for the score and for the overall CMR Mass Score (Supplementary Table S5).In detail, interobserver Cohen's κ was 0.72, 0.75, 0.87, 0.74, 0.86, and 0.80 for infiltration, polylobate mass, pericardial effusion, sessile, first-pass contrast perfusion, and heterogeneity enhancement respectively, indicating good or excellent reliability for all parameters.S1.Baseline clinical and laboratory characteristics of study population stratified according to benign or malignant cardiac masses.

Table S2 .
Comparison of echocardiographic features between benign or malignant masses.